A seizure may be characterized as abnormal or excessive synchronous activity in the brain. At the beginning of a seizure, neurons in the brain may begin to fire at a particular location. As the seizure progresses, this firing of neurons may spread across the brain, and in some cases, many areas of the brain may become engulfed in this activity. Seizure activity in the brain may cause the brain to send electrical signals through the peripheral nervous system activating different muscles of the body. Other seizure events, such as psychogenic or non-epileptic seizures (PNES) may be characterized by abnormal muscle movements, but may not necessarily involve the same type of asynchronous brain activity as may more common seizure events.
Techniques designed for studying and monitoring seizures have typically relied upon electroencephalography (EEG), which characterizes electrical signals using electrodes attached to the scalp or head region of a seizure-prone individual or seizure patient. In EEG, electrodes may be positioned so as to measure such activity; that is, electrical activity originating from neuronal tissue. Alternatively, electromyography (EMG) may be used for seizure detection. In EMG, an electrode may be placed on or near the skin, over a muscle, to detect electrical activity resulting from muscle fiber activation.
Detecting an epileptic seizure using EEG typically requires attaching many electrodes and associated wires to the head and using amplifiers to monitor brainwave activity. The multiple EEG electrodes may be very cumbersome and generally require some technical expertise to apply and monitor. Furthermore, confirming a seizure may require observation in an environment provided with video monitors and video recording equipment. Unless used in a staffed clinical environment, such equipment may not be intended to determine if a seizure is in progress, but rather provide a historical record of the seizure after the incident. Such equipment is usually meant for hospital-like environments where a video camera recording or caregiver's observation may provide corroboration of the seizure and is typically used as part of a more intensive care regimen such as a hospital stay for patients who experience multiple seizures.
Even when monitoring a patient using EEG and the patient's environment with video recording, it may be difficult to characterize all types of seizure-related events that a patient may experience. For example, although specialized caregivers or epileptologists may sometimes be able to differentiate between some types of seizures which may result from epilepsy, such as generalized tonic-clonic (GTC) seizures, and other types of related events, such as PNES events, missed or inaccurate diagnosis may still occur. Additionally, other caregivers, who may not have the same level of expertise and training as specialized epileptologists, generally cannot identify differences between GTC and PNES seizures. This is particularly troubling because delayed or incorrect diagnosis of PNES may be costly to hospitals, and incorrect or incomplete diagnosis may prevent patients from receiving proper care. Accordingly, methods designed to verify and/or assist caregivers in making a proper diagnosis of epilepsy and/or other related conditions would be extremely useful.
Ambulatory devices for diagnosis of seizures may also be primarily EEG-based, but because of the above shortcomings those devices are not designed or suitable for long-term home use or daily wearability. Other seizure alerting systems may operate by detecting motion of the body, usually the extremities. Such systems may generally operate on the assumption that while suffering a seizure, a person will move erratically and violently. For example, accelerometers may be used to detect violent extremity movements. However, depending upon the type of seizure, this assumption may or may not be true. Electrical signals sent from the brain during some seizures may be transmitted to many muscles simultaneously, which may result in muscles fighting each other and effectively canceling out violent movement. In other words, the muscles may work to make the person rigid rather than cause actual violent movement. Thus, some seizures may not be consistently detected with accelerometer-based detectors.
Ambulatory devices for diagnosis of seizures are generally not suited to grade seizures based on intensity, nor are they suited to differentiate seizure-related signals based on event type. Rather, different types of seizures may often be grouped together. For example, suitable methods for characterization of data collected using ambulatory devices and for generating statistical information useful to caregivers are noticeably deficient or missing.
Accordingly, there is a need for epileptic seizure detection methods and apparatuses that can be used in non-institutional or institutional environments without many of the cumbersome electrodes to the head or extremities. There is further a need for detection methods that are suited to analyze seizures by type and/or intensity in order to characterize seizure events to help medically and surgically manage patient care. For example, robust methods for differentiating GTC seizures from PNES seizures may greatly improve patient care. There is further a need for methods that are suited to characterize seizures using automated or semi-automated algorithms including ones that may be used to rapidly search through and characterize extensive patient data, such as may be produced from personal mobile devices. There is further a need for systems and methods useful in aiding caregivers in making and/or verifying a proper diagnosis of epilepsy and/or other related conditions.